Search Results (5,357)

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, primarily driven by chronic inflammation from viral hepatitis, metabolic dysfunction, alcohol-induced liver disease, and cirrhosis. Conventional therapies often fail in advanced stages, highlighting the need for mechanism-based, precision-guided interventions. Plant-derived secondary metabolites represent a promising class of bioactive compounds with structural diversity, multitarget activity, anti-inflammatory effects, and favorable toxicity profiles. This review follows a semi-systematic narrative that synthesizes preclinical and experimental evidence on the anti-inflammatory and anticancer properties of key phytochemicals, including epigallocatechin-3-gallate, galangin, resveratrol, quercetin, curcumin, berberine, genistein, and thymoquinone. These compounds consistently modulate critical inflammation-driven signaling pathways, PI3K/AKT/mTOR, NF-κB, JAK/STAT, Wnt/β-catenin, and MAPK, resulting in apoptosis induction, cell cycle arrest, inhibition of angiogenesis, and reduced invasion and metastasis in multiple HCC models. Despite strong preclinical evidence, clinical translation remains limited by variable bioavailability, incomplete safety data, and insufficient human studies. A staged development strategy is recommended: standardized formulations, Good Laboratory Practice-compliant pharmacokinetic/toxicology studies, validation in patient-derived models, and early-phase, biomarker-guided clinical trials with combination therapy arms. Addressing regulatory, manufacturing, and quality control considerations will be essential for advancing these compounds as adjuvant or complementary agents in precision HCC therapy. Full article

Snakebite envenoming is classified as a Neglected Tropical Disease and causes mortality, morbidity, and economic impacts for hundreds of thousands of people per year, particularly in tropical, low- and middle-income countries. Most research on snakebite interventions focuses on improving clinical management rather than bite prevention. However, prevention may provide a better mechanism to minimise snakebite impacts, particularly in rural areas where access to effective medical treatment is limited. This study reports on the preliminary testing phase of a participatory workshop intervention run in rural Uganda in 2022–23, which used a community engagement approach designed to reduce snakebites through discussing snake behaviour and biology. A mixed methods survey and semi-structured interviews were conducted, both with workshop attendees and non-attendees, after the delivery of the workshops. We found that a fearful attitude toward snakes often led to human–snake conflict, with snake killings occurring commonly, and some bites occurring during attempted killings. Workshops appeared to challenge negative attitudes, as understanding snake behaviour seemed to build compassion toward snakes and therefore has the potential to reduce human–snake conflict. Those who attended workshops were more likely to suggest ‘giving snakes space,’ rather than attempting to kill them, and were more likely to suggest hospital treatment if bitten. We also found that many effective methods for snakebite prevention are already known to the community, but those who attended the workshop were aware of a wider range of prevention methods and were more likely to implement less ecologically damaging and more effective strategies. This emphasises that appropriate knowledge resides within the community to prevent snakebites, and so community engagement approaches can improve prevention practices while recognising that the ownership and knowledge for such changes is generated by the local people themselves. Full article

Background/Objectives: Safe delivery and correct identification of newborns are critical aspects of healthcare systems globally. The accreditation of healthcare and standards regulation significantly promotes the adoption of modern technologies to address risks related to infant abduction and misidentification. The effectiveness and extent of these mandates vary across settings and countries. Therefore, this study aims to map and explore modern technologies used for safe newborn delivery and correct identification aligned with healthcare accreditation and regulatory frameworks. Methods: This review adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis extension for scoping reviews (PRISMA-ScR) guidelines. The Problem, Intervention, Comparison, and Outcome (PICO) framework was employed to facilitate the development of the research question. This study examined studies reporting technologies such as radio frequency identification (RFID), biometric identification, and real-time monitoring across healthcare settings for infant protection through the Normalization Process Theory (NPT). Among three databases and search engines (PubMed, Google Scholar, and Web of Science). The risk of bias for each study was assessed using the AACODS Checklist, SQUIRE 2.0 Checklist, TIDieR Checklist, and JBI tools. Results: Out of 8753 records, only 27 reports were eligible to be included in this review. The most frequently reported technologies were RFID systems (11 studies, 37.9%) and biometric systems such as footprint and facial recognition (6 studies, 20.7%). Despite strong technological potential, many healthcare institutions struggled with the adoption of infant protection technologies. Accreditation systems among the high-resource settings actively mandate advanced technologies and support the integration of staff training and simulation drills. Comparably, middle- and low-income regions usually face challenges related to regulatory enforcement, infrastructure, staff readiness, and limited adoption of modern technologies. Conclusions: Accreditation and standards development are critical catalysts for the adoption of modern infant protection technology. Standards must be comprehensible, adaptable, and supported by investment in human resources and infrastructure. Future regulation must focus on strengthening enforcement, continuous quality improvement, and capacity building to achieve sustainable protection across the world. Full article

Background/Objectives: Legumes, a significant source of plant-based protein, play a crucial role in diets across Portugal and Spain, contributing to both human and animal nutrition. As plant-based diets gain traction, various legumes like chickpeas, lentils, and beans have risen in popularity. However, fava beans remain underutilized compared to these varieties. This study explores stakeholder perspectives on the factors influencing the lower consumption rates of fava beans in the Iberian Peninsula, despite their nutritional and environmental benefits. Methods: An exploratory qualitative study was conducted using semi-structured interviews with diverse stakeholders, including nutritionists, retailers, farmers, catering professionals, and both vegetarian and non-vegetarian consumers in Portugal and Spain. Results: Our findings highlight a perceived lack of visibility of fava beans in supermarkets and on influential social media platforms, which often shape consumer preferences. Seasonal availability further contributes to the limited consumption, as people tend to purchase fava beans only when they are more prominent in markets. Addressing local challenges to legume production and consumption can pave the way for effective interventions to increase the intake of these sustainable foods. This study suggests promoting fava beans as a locally cultivable option, which could reduce reliance on imports and enhance regional agricultural output. Interviewees suggested using targeted promotional tactics, such as short videos, cooking demonstrations, and influencer marketing on social media, as effective means to boost fava bean consumption. Conclusions: These exploratory findings indicate that such strategies may foster a more positive perception and integrate fava beans into everyday diets in the region. Full article

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra (SN). Because current therapeutics have limited efficacy once PD is fully developed, it is crucial to start disease-modifying interventions during the prodromal stage of PD. In the present study, we aimed to evaluate whether intranasally delivered human umbilical cord mesenchymal stem cells (hUC-MSCs) have an efficacy in the rotenone-induced prodromal PD-like phenotype mouse model. Methods: To produce the prodromal PD mouse model, C57BL/6 mice were treated with intraperitoneal (i.p.) rotenone for 1 or 2 weeks. hUC-MSCs or PBS were delivered intranasally for 1 or 2 weeks with rotenone injection. We subsequently performed behavioral assessments to evaluate motor and non-motor features, followed by pathological analyses of the mouse brains. Results: Intranasal administration of hUC-MSCs restored motor performance and protected dopaminergic neurons in the SN of mice treated with rotenone for 2 weeks. In the 1-week rotenone mice, hUC-MSCs treatment ameliorated depressive-like behaviors and attenuated olfactory dysfunction. Furthermore, intranasal hUC-MSC treatment suppressed the accumulation of protein aggregates in the brains of mice, which is associated with enhanced autophagic function, as indicated by increased LC3B and normalization of LAMP2A protein expression. Conclusions: Our data demonstrate that intranasal administration of hUC-MSCs improves non-motor symptoms at early time points and attenuates progression to nigrostriatal loss and motor deficits in the rotenone-induced PD mouse model. These findings support the potential of a non-invasive, prodromal-stage intervention to modulate early pathological progression in PD. Full article

Background: Exercise-induced fatigue (EIF) impairs performance and recovery and may contribute to overreaching/overtraining and adverse health outcomes. Beyond classical explanations (substrate depletion, metabolite accumulation, oxidative stress), accumulating evidence indicates that the gut microbiota modulates fatigue-related physiology through metabolic, immune, barrier, and neurobehavioral pathways. Methods: We conducted a structured narrative review of PubMed and Web of Science covering 1 January 2015 to 30 November 2025 using predefined keywords related to EIF, gut microbiota, recovery, and nutritional interventions. Human studies, animal experiments, and mechanistic preclinical work (in vivo/in vitro) were included when they linked exercise load, microbial features (taxa/functions/metabolites), and fatigue-relevant outcomes. Results: Across models, high-intensity or prolonged exercise is consistently associated with disrupted gut homeostasis, including altered community structure, reduced abundance of beneficial taxa, increased intestinal permeability, and shifts in microbial metabolites (e.g., short-chain fatty acids). Evidence converges on four interconnected microbiota-mediated pathways relevant to EIF: (1) energy availability and metabolic by-product clearance; (2) redox balance and inflammation; (3) intestinal barrier integrity and endotoxemia risk; and (4) central fatigue and exercise motivation via microbiota–gut–brain signaling. Nutritional strategies—particularly targeted probiotics, prebiotics/plant polysaccharides, and selected bioactive compounds—show potential to improve fatigue biomarkers and endurance-related outcomes, although effects appear context-dependent (exercise modality, baseline fitness, diet, and baseline microbiota). Conclusions: Current evidence supports a mechanistic role of the gut microbiota in EIF and highlights microbiota-targeted nutrition as a promising adjunct for recovery optimization. Future work should prioritize causal validation (e.g., fecal microbiota transplantation and metabolite supplementation), athlete-focused randomized trials with standardized fatigue endpoints, and precision approaches that stratify individuals by baseline microbiome features and training load. Full article

Background/Objectives: The prevalence of the commensal gut bacterium species, Phascolarctobacterium faecium, has been associated with normal weight in humans. Preclinical evidence suggests that the strain P. faecium DSM 32890 exerts beneficial effects on metabolic and immune function in diet-induced obesity. Herein, we aimed to evaluate the safety and tolerability of this strain in a preclinical study and a pilot interventional trial in humans. Methods: A repeated-dose oral toxicity study of 28 days was performed in Wistar rats (male and female), during which adverse signs and clinical outcomes were assessed, along with histological, hematologic, biochemical, and immune markers. Subsequently, a pilot human intervention trial was conducted, including 20 participants (11 overweight and 9 normal weight) who received P. faecium DSM 32890 daily for 15 days. Body composition, dietary intake, physical activity, clinical data, perceived health, gastrointestinal symptoms, and blood analyses were assessed to determine tolerability and identify potential adverse effects. Results: In rats, the administration of the bacterium did not cause behavioral, physiological, histologic, immune, or biochemical alterations. In humans, there was no evidence of adverse effects on general health, hematological and biochemical profiles, bowel habits, or gastrointestinal symptoms. Overweight participants experienced reductions in flatulence and nausea after the intervention. Conclusions: The consumption of P. faecium DSM 32890 did not raise safety concerns and was well tolerated in rats and humans. The findings represent a step forward in the path toward future, longer-term studies to explore the potential efficacy. Full article

Rotating machinery are essential elements in industrial systems and strongly present aboard vessels and maritime platforms, whose unexpected failure can lead to significant economic and operational losses, both for the maritime industry and for industry in general. Condition Monitoring (CM), through the analysis of specific parameters, aims to assess equipment health and enable the early detection of deviations from normal operating conditions. Among existing techniques, vibration analysis stands out for its effectiveness. However, when applied to naval environments, it requires human resources and equipment that are not always prepared or available. Aligned with the principles of Industry 4.0, maintenance has been integrating technologies that enhance data collection and analysis, becoming more autonomous and intelligent. The integration of Machine Learning (ML) into CM offers an alternative to conventional approaches, enabling systems to learn real operating behavior and recognize fault patterns with high accuracy and reduced human intervention. Addressing a real industrial challenge, this paper proposes an automatic framework for fault detection and diagnosis using ML models. As a case study, vibration data from rotating machinery were analyzed, encompassing common faults such as unbalance, misalignment, and the combination of both. The obtained results highlight the potential of the proposed framework for CM in maritime environments, modernizing it with new trends and making it more autonomous, efficient, and less dependent on specialized knowledge. Full article

This study proposes a comprehensive framework for evaluating New Quality Productive Forces (NQPF) in forestry, with a focus on human capital, technological innovation, and ecological efficiency as key drivers of sustainable development. Despite moderate growth in NQPF development in China from 2013 to 2022, significant regional disparities persist, with eastern regions outperforming the western regions in terms of forestry productivity and technological adoption. To assess NQPF development, we employ the improved variable-weight matter-element extension model (IVWME), combined with spatial correlation analysis, Gini coefficient measurement, and obstacle degree analysis. The results indicate that, while NQPF development remains stable, eastern regions benefit from superior access to technology and human capital, while western regions face challenges such as slower technological progress and limited labor force development. This study highlights the need for targeted policy interventions that focus on enhancing human capital, promoting technological innovation, and improving regional coordination. The framework provides valuable insights for policymakers in China and other countries facing similar challenges in sustainable forestry development, offering a practical approach to advancing forestry modernization through NQPF. Full article

A hybrid AI and LLM-enabled architecture is presented for real-time decision support in industrial batch processes, where supervision still relies heavily on human operators and ad hoc SCADA logic. Unlike algorithmic contributions proposing novel AI methods, this work addresses the practical integration and deployment challenges arising when applying existing AI techniques to safety-critical industrial environments with legacy PLC/SCADA infrastructure and real-time constraints. The framework combines deterministic rule-based agents, fuzzy and statistical enrichment, and large language models (LLMs) to support monitoring, diagnostic interpretation, preventive maintenance planning, and operator interaction with minimal manual intervention. High-frequency sensor streams are collected into rolling buffers per active process instance; deterministic agents compute enriched variables, discrete supervisory states, and rule-based alarms, while an LLM-driven analytics agent answers free-form operator queries over the same enriched datasets through a conversational interface. The architecture is instantiated and deployed in the Clean-in-Place (CIP) system of an industrial beverage plant and evaluated following a case study design aimed at demonstrating architectural feasibility and diagnostic behavior under realistic operating regimes rather than statistical generalization. Three representative multi-stage CIP executions—purposively selected from 24 runs monitored during a six-month deployment—span nominal baseline, preventive-warning, and diagnostic-alert conditions. The study quantifies stage-specification compliance, state-to-specification consistency, and temporal stability of supervisory states, and performs spot-check audits of numerical consistency between language-based summaries and enriched logs. Results in the evaluated CIP deployment show high time within specification in sanitizing stages (100% compliance across the evaluated runs), coherent and mostly stable supervisory states in variable alkaline conditions (state-specification consistency ${\Gamma }_s\ge 0.98$), and data-grounded conversational diagnostics in real time (median numerical error below 3% in audited samples), without altering the existing CIP control logic. These findings suggest that the architecture can be transferred to other industrial cleaning and batch operations by reconfiguring process-specific rules and ontologies, though empirical validation in other process types remains future work. The contribution lies in demonstrating how to bridge the gap between AI theory and industrial practice through careful system architecture, data transformation pipelines, and integration patterns that enable reliable AI-enhanced decision support in production environments, offering a practical path toward AI-assisted process supervision with explainable conversational interfaces that support preventive maintenance decision-making and equipment health monitoring. Full article

While global climate adaptation goals are well-established, their translation into neighborhood-scale spatial reality remains underexplored, creating a critical knowledge gap regarding the social acceptability of specific interventions. This study addresses this “governance–perception mismatch” through a case study of Caferağa, a high-density coastal district in Istanbul. By surveying 104 “ground-floor interface” stakeholders, the research investigates the extent to which spatial strategies are integrated and how they are perceived by local users. The findings reveal three significant patterns: (1) an “implementation gap”, where a majority of respondents (51.0%) report no effective adaptation measures despite strongly prioritizing green infrastructure (38.5%) over water management solutions (13%); (2) a “participation paradox”, evidenced by a stark divergence between high willingness to engage (73.1%) and negligible perceived involvement; and (3) the conceptual validation of “informed cynicism”, where higher education levels correlate with deeper institutional distrust due to the recognized inadequacy of current actions. The study concludes that in centralized planning systems, the structural exclusion of high-human-capital stakeholders transforms potential co-production into active alienation. Full article

Geomorphological change is a fundamental consequence of high-magnitude flood events, as extreme hydraulic forcing can rapidly reshape river channels, redistribute sediment, and alter floodplain connectivity. This study applies multi-temporal UAS-based Structure-from-Motion (SfM) photogrammetry to quantify flood-induced geomorphological changes along two representative reaches of the Lilas River (Evia Island, Central Greece) affected by the extreme August 2020 flash flood. High-resolution aerial surveys were conducted prior to the event (June 2018) and shortly after the flood (September 2020), producing Digital Surface Models (DSMs) and orthomosaics with a ground sampling distance of ~2.5 cm. Differential DSM analysis reveals pronounced spatial heterogeneity in erosion and deposition, with net erosional lowering locally exceeding 7 m and depositional aggradation reaching up to ~5 m after accounting for vegetation effects. Channel widening was the dominant response, with cross-sectional widths increasing by a factor of three to nine at selected locations, driven primarily by lateral bank erosion. The results highlight the strong interaction between extreme hydrological forcing, loose alluvial sediments, vegetation removal, and human interventions such as roads and engineered terraces. The study demonstrates how repeatable UAS–SfM workflows can provide quantitative evidence to support post-flood assessment, guide infrastructure adaptation, and inform river restoration and flood risk management in Mediterranean catchments prone to extreme events. Full article

Aim: Finding innovative paraclinical parameters is necessary for advancing clinical research, in obstetrics and gynecology for subjective symptoms such as pain, especially in patients with a weakened immune system, following, for example, different obstetrical and gynecological surgeries. The purpose of this study was to analyze if genetic markers can correlate with the postoperative outcome and surgical results in obstetrics and gynecology. We wanted to analyze whether patients carrying the G gene responsible for the A11G polymorphism of the OPRM1 receptor really have a higher need for analgesic doses for postoperative pain control, depending on the histopathological results, benign or malignant tumors, dimensions of tumors, type of incision performed, and hospitalization period. Materials and Methods: We analyzed 111 patients, including both obstetrical and gynecological cases. Blood samples (2 mL) for DNA analysis were obtained before surgery in a tube containing EDTA as an anticoagulant and immediately stored at −20 °C until required for further use. The blood samples, which were collected at the time of intravenous cannulation before surgery, were analyzed for the presence of SNP 118AG. Results: We examined the mutation of the opioid receptor called OPRM1 for the polymorphism noted with AG with a plus sign (+) (present) in 24.3% of the patients, with a minus sign (−) (AA) (absent) in 66.7% of the patients, and with a result with both genes modified (GG) in 9%. We correlated the data obtained in histopathology and clinical anamnesis with these results. The OPRM1(+) morphine receptor mutation was more frequently encountered in patients with biopsy uterine curettage (60%) with benign results in anatomopathology, uterine myomectomy of at least 5 cm fibromas with benign results in anatomopathology (50%), Madden mastectomy (50%), interventional hysteroscopy (33.3%) with extraction of benign tumors such as polyps or endometrial hyperplasia, caesarean section-associated surgeries (20.7%), and ovarian cystectomy (20%) (p = 0.048) that had a final benign anatomopathology result. Conclusions: Pain management in the postoperative phase is difficult for clinicians because of the response of patients to opioid therapy. Some of this variability in pain response may result from single nucleotide polymorphisms (SNPs) in the human opioid receptor mu-1 (OPRM1) that alter receptor binding or signal transduction. Part of the difficulty in identifying genes and variants that affect postsurgical pain is the inconsistent findings and poor replicability of results. Full article

Artificial intelligence (AI) is rapidly reshaping gastrointestinal (GI) surgery by enhancing decision-making, intraoperative performance, and postoperative management. The integration of AI-driven systems is enabling more precise, data-informed, and personalized surgical interventions. This review provides a state-of-the-art overview of AI applications in GI surgery, organized into four key domains: surgical simulation, surgical computer vision, surgical data science, and surgical robot autonomy. A comprehensive narrative review of the literature was conducted, identifying relevant studies of technological developments in this field. In the domain of surgical simulation, AI enables virtual surgical planning and patient-specific digital twins for training and preoperative strategy. Surgical computer vision leverages AI to improve intraoperative scene understanding, anatomical segmentation, and workflow recognition. Surgical data science translates multimodal surgical data into predictive analytics and real-time decision support, enhancing safety and efficiency. Finally, surgical robot autonomy explores the progressive integration of AI for intelligent assistance and autonomous functions to augment human performance in minimally invasive and robotic procedures. Surgical AI has demonstrated significant potential across different domains, fostering precision, reproducibility, and personalization in GI surgery. Nevertheless, challenges remain in data quality, model generalizability, ethical governance, and clinical validation. Continued interdisciplinary collaboration will be crucial to translating AI from promising prototypes to routine, safe, and equitable surgical practice. Full article

Background/Objectives: Human papillomavirus (HPV) is a major cause of cervical, penile, anal, and oropharyngeal cancers. HPV vaccination is the most effective public health strategy for its prevention. Understanding the factors influencing vaccination intentions is critical for developing effective public health policies and improving population-level vaccine uptake. Therefore, in this scoping review, we aimed to examine HPV vaccination research conducted in Korea, identify common trends and gaps in study populations and influencing factors, and provide evidence-based recommendations for public health policies. Methods: We systematically searched four Korean databases—Research Information Sharing Service (RISS), DBpia, Korean Studies Information Service System (KISS), and National Digital Science Library (NDSL)—for studies published from their respective inception dates to January 2025, using “human papillomavirus,” “HPV,” “vaccination,” and “intention” as keywords. Thirty-six studies were ultimately included. Study characteristics, populations, theoretical frameworks, and key variables were extracted and analyzed using descriptive statistics and content analysis. Results: Of the included studies, 61.1% and 38.9% targeted vaccination-eligible individuals (adolescents and adults) and parents/guardians, respectively, with 50% focusing exclusively on women. The major factors influencing HPV vaccination intention were attitude (47.2%), subjective norms (38.9%), and perceived behavioral control (30.9%). Attitude and knowledge were critical for vaccination-eligible individuals (Direct group), whereas subjective norms were key for parents/guardians (Indirect group). Conclusions: Korean HPV vaccination intention research has predominantly focused on women and parents, with insufficient attention to adolescents and men. Public health strategies must employ multilevel interventions tailored to each group’s decision-making structures, including school-based programs for adolescents, gender-inclusive policies for men, and community-based approaches to address social norms among parents. These findings provide evidence for policy development aligned with the WHO cervical cancer elimination goals. Full article